Bio-inspired design represents an important engineering philosophy. However, execution of bio-inspired concepts is rarely a straight-forward endeavor.
In the matter of depth perception, for example, humans judge depth mostly from binocular stereoscopic vision, rooted in parallax. Many animals, such as octopi, do not have the same degree of binocular vision and instead employ motion parallax by moving their heads side-to-side to judge distance to an object to estimate distance to objects of interest. Even though each approach is well known, a plethora of patents have been issued involving computer advancements allowing for so-called “machine vision” based in stereoscopic depth imaging.
A more recent (and unique) example of bio-inspired design is presented in the Lytro, Inc. camera system. Taking cues from insectoid compound eyes, a sensor images with a multitude of subarrays. In reference to US Publication No. 2007/025207 to Ng et al., each subarray is associated with its own microlens to capture a small portion of the overall scene, with a portion that overlaps slightly with that of the neighboring subarrays. By comparing the differences between the captured images to determine the angle of incidence of the light detected at the different locations on the focal plane, a system can judge the distance of elements in the subject to reconstruct image focus at different depths in an image field. The approach is computationally-intensive and packaged in unconventional hardware configurations (e.g., as compared to typical commercially-available camera options).
Another process with antecedent in nature involves depth determination/estimation from the blurring of out-of-focus images. As reported by Nagata, et al. in “Depth Perception from Image Defocus in a Jumping Spider,” Science 27 Jan. 2012: Vol. 335 no. 6067 pp. 469-471, the principle eyes of the so-called “Jumping Spider” have a unique retina with four tiered photoreceptor layers, on each of which light of different wavelengths is focused. The effect of layer separation, compounded by chromatic aberration of the lens, ensures that the second-deepest layer always receives defocused images. Thus, depth imaging related to image defocus was demonstrated.
Other systems describing depth-from-defocus systems are presented in each of Chaudhuri et al., “Depth From Defocus: A Real Aperture Imaging Approach,” Springer, Mar. 26, 1999, U.S. Pat. No. 6,229,913 to Nayar and U.S. Pat. No. 7,711,201 to Wang, et al. and US Publication No. 2008/0232680 to Berestov, et al.
Potential depth-from-defocus imaging advantages include the ability to recover absolute depth of the scene with just two defocused images, avoidance of correspondence and occlusion problems, and depth recovery as parallel involving only simple computations without search. However, Chaudhuri comments that its estimates of depth are less accurate compared to stereo and motion-based techniques with existing approaches. Berestov, et al. and Nayar describe multi-sensors systems, with the latter additionally reliant on projected patterns of light to achieve its goals. Wong, et al. describes a system in which depth information is acquired by moving the lens a short distance and acquiring multiple images with different blur quantities.